6 papers · 1 filter
Graph-Assisted Culturally Adaptable Idiomatic Translation for Indic Languages
Pratik Rakesh Singh, Kritarth Prasad, Mohammadi Zaki +1
Translating multi-word expressions (MWEs) and idioms requires a deep understanding of the cultural nuances of both the source and target languages. This challenge is further amplif…
In-Domain African Languages Translation Using LLMs and Multi-armed Bandits
Pratik Rakesh Singh, Kritarth Prasad, Mohammadi Zaki +1
Neural Machine Translation (NMT) systems face significant challenges when working with low-resource languages, particularly in domain adaptation tasks. These difficulties arise due…
Faster Machine Translation Ensembling with Reinforcement Learning and Competitive Correction
Kritarth Prasad, Mohammadi Zaki, Pratik Singh +1
Ensembling neural machine translation (NMT) models to produce higher-quality translations than the individual models has been extensively studied. Recent methods typically empl…
Enhancing Entertainment Translation for Indian Languages using Adaptive Context, Style and LLMs
Pratik Rakesh Singh, Mohammadi Zaki, Pankaj Wasnik
We address the challenging task of neural machine translation (NMT) in the entertainment domain, where the objective is to automatically translate a given dialogue from a source la…
Enhancing Whisper's Accuracy and Speed for Indian Languages through Prompt-Tuning and Tokenization
Kumud Tripathi, Raj Gothi, Pankaj Wasnik
Automatic speech recognition has recently seen a significant advancement with large foundational models such as Whisper. However, these models often struggle to perform well in low…
Efficient infusion of self-supervised representations in Automatic Speech Recognition
Darshan Prabhu, Sai Ganesh Mirishkar, Pankaj Wasnik
Self-supervised learned (SSL) models such as Wav2vec and HuBERT yield state-of-the-art results on speech-related tasks. Given the effectiveness of such models, it is advantageous t…